Green N-CQDs from Cotton Waste for “Turn-On” Fluorescent Biosensing of Levofloxacin in Food and Biological Matrices
Abstract
Rapid, sensitive monitoring of fluoroquinolone residues is essential for medicine and the food industry. We report a “turn-on” fluorescent biosensor based on nitrogen-doped carbon quantum dots (N-CQDs) prepared by a one-pot hydrothermal route using cotton waste as the carbon source and o-phenylenediamine as the nitrogen passivator. The N-CQDs display a quantum yield of 42% and stable photoluminescence. Levofloxacin binds to surface functional groups on the N-CQDs and inhibits photoinduced electron transfer (PET), restoring radiative decay and enhancing fluorescence. The sensor affords an ultralow LOD of 0.55 nM and a linear range of 1.83–40.00 nM with high selectivity against common interferents. The method was successfully applied to pharmaceutical tablet extracts, raw milk, chicken meat, and urine, achieving excellent spike-recovery and precision. This work demonstrates a sustainable, low-cost nanosensor that converts agricultural waste into a high-performance optical biosensing platform for drug-residue screening across clinically and industrially relevant matrices. The approach is readily scalable and compatible with routine fluorescence instrumentation, supporting rapid decision-making in food safety and healthcare settings.
Read the paper
Related studies
- Ferulic acid regulates the AKT/GSK-3β/CRMP-2 signaling pathway in a middle cerebral artery occlusion animal model
- Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure–Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli
- Photochemical behavior of levofloxacin
- Correlation Between Dissolution Profiles of Salt-Form Drugs in Biorelevant Bicarbonate Buffer and Oral Drug Absorption: Importance of Dose/ Fluid Volume Ratio
- Evaluation of the synergistic potential and mechanisms of action for de novo designed cationic antimicrobial peptides
- Synthesis of [11C]levofloxacin
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.